IBM Spectrum Computing and Cloudera Data Platform are competing products utilized for data management and analytics. Cloudera Data Platform seems to have the upper hand due to its robust feature set and extensive integration options.
Features: IBM Spectrum Computing offers resource management, workload optimization, and intelligent workload management feature connected to the cloud. Cloudera Data Platform provides seamless data analytics capabilities, strong integration and scalability, and features like distributed data storage using HDFS and YARN for resource management.
Room for Improvement: IBM Spectrum Computing requires simplification in clustering compute resources and support for more straightforward interfaces. Additionally, refining predictive analytics and diagnostics tools would benefit users. Cloudera Data Platform could improve in ease of deployment, enhance user interfaces for better usability, and streamline security features for even more granular access control.
Ease of Deployment and Customer Service: IBM Spectrum Computing has a straightforward deployment process and efficient customer service praised for being responsive. For Cloudera Data Platform, deployment is more complex but supported by comprehensive documentation. Despite this complexity, it often delivers effective and scalable solutions once deployed.
Pricing and ROI: IBM Spectrum Computing is known for competitive pricing and favorable ROI, especially in resource management. Cloudera Data Platform may have a higher setup cost, but its advanced features and scalability offer substantial ROI that justifies the investment for many enterprises.
| Product | Market Share (%) |
|---|---|
| Cloudera Data Platform | 7.6% |
| Palantir Foundry | 15.6% |
| Informatica Intelligent Data Management Cloud (IDMC) | 10.8% |
| Other | 66.0% |
| Product | Market Share (%) |
|---|---|
| IBM Spectrum Computing | 4.3% |
| Cloudera Distribution for Hadoop | 15.1% |
| HPE Data Fabric | 14.9% |
| Other | 65.7% |
| Company Size | Count |
|---|---|
| Small Business | 8 |
| Midsize Enterprise | 7 |
| Large Enterprise | 26 |
| Company Size | Count |
|---|---|
| Small Business | 3 |
| Midsize Enterprise | 1 |
| Large Enterprise | 6 |
Cloudera Data Platform offers a powerful fusion of Hadoop technology and user-centric tools, enabling seamless scalability and open-source flexibility. It supports large-scale data operations with tools like Ranger and Cloudera Data Science Workbench, offering efficient cluster management and containerization capabilities.
Designed to support extensive data needs, Cloudera Data Platform encompasses a comprehensive Hadoop stack, which includes HDFS, Hive, and Spark. Its integration with Ambari provides user-friendliness in management and configuration. Despite its strengths in scalability and security, Cloudera Data Platform requires enhancements in multi-tenant implementation, governance, and UI, while attribute-level encryption and better HDFS namenode support are also needed. Stability, especially regarding the Hue UI, financial costs, and disaster recovery are notable challenges. Additionally, integration with cloud storage and deployment methods could be more intuitive to enhance user experience, along with more effective support and community engagement.
What are the key features?Cloudera Data Platform is implemented extensively across industries like hospitality for data science activities, including managing historical data. Its adaptability extends to operational analytics for sectors like oil & gas, finance, and healthcare, often enhanced by Hortonworks Data Platform for data ingestion and analytics tasks.
IBM Spectrum Computing uses intelligent workload and policy-driven resource management to optimize resources across the data center, on premises and in the cloud. Now up to 150X faster and scalable to over 160,000 cores, IBM provides you with the latest advances in software-defined infrastructure to help you unleash the power of your distributed mission-critical high performance computing (HPC), analytics and big data applications as well as a new generation open source frameworks such as Hadoop and Spark.
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